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survival guide for venture investors allocating to prediction markets supercycle:
- if startup is pushing novel scoring rules or AMM designs, ie some derivative of LMSR, you can prob assume they're at least 6-8 months away from any kind of meaningful execution
- user generated markets is a promising hypothesis on aggregate, but don't be led to believe creator monetization is solved here. the economics of forming liquidity for novel markets where a prediction market is the first point of price discovery are rough
- prediction markets inherited a "subsidy" culture from academia. that is, a lot of academics intended for prediction markets to be a tool that ie companies could use to put up a bounty for keen forecasters to discover the aggregated outputs of their models. that means market creators (or initial liquidity providers to automated mechanisms) are incurring heavy losses. these automated mechanisms also produce a lot of one sided flow that couldn't be supported by orderbooks, and the value of the information produced by this flow certainly diminishes
- on the other side, orderbooks are hard to bootstrap for these markets. this goes back to the prediction market being the first point of price discovery. this price discovery is extremely subjective. compare trying to put a price on if Trump is on the Epstein list with if BTC will be above $118k at the end of the trading day. for the latter you can simply use options for pricing & hedging
- for more subjective markets, not only is it hard to price them initially, but it's hard to build models and bots for position & risk management, so it requires a lot of manual effort and attention to provide liquidity to those markets
- this has gave rise to a class of prediction market makers, who are retail whales dedicated almost full time to trying to price these things & manually managing their orders. effectively the kind of super forecaster service provider academia always anticipated to play a role in prediction markets. due to design of LP rewards program used by Polymarket and manual management constraints, traders optimize for having their orders filled as less as possible and extracting maximum rewards instead of prioritizing healthy spreads and seamless order execution
- now, what's the catch with service providers dreamt up by academia? well, you have to pay them handsomely of course. Polymarket is burning $600k per month in USDC on rewards with no fee, suggesting extraordinarily high expectations for how this pricing information will become valuable in future. it is arguable that this is a handsome premium being paid for the service provided
- so, prediction markets are doomed? not exactly. I would break up prediction markets into sub categories, denominated by retail risk appetite. to us, the largest sources of retail risk appetite are options / perps / memecoins trading and sports betting. market makers paid $1.2B to retail brokers for retail options order flow in Q1. American consumer bet over $150B on sports in 2024 and monetization rate is very high (>$10B). these 2 buckets alone will wind up to be the most consequential in our opinion, and event contracts have a real opportunity to eat sports betting & traditional derivatives and even grow the pie. US election is a standout standalone season that can attract a lot of attention and volumes, but lacks fast and reoccurring nature retail love. there is also demand for global elections and war markets driven by information asymmetry, but I can't see them ever being regulated in the US. everything else is a philosophical crusade that is transferring wealth from venture capital to a small community of super forecasters in the form of liquidity subsidies with little thought on how the market can evolve or how valuable that service being provided actually is
so, how to not only survive but thrive in the prediction markets supercycle? don't buy into stuffy failed infra founders AMM designs, they suck. don't join the crusade of paying for informational markets that don't have objective demand for their outputs. bet big on sports and options and teams that have high engagement, retention & demand with sustainable economics. don't chase shiny objects that are ultimately just a mirage. it is the simple & boring ideas that are most powerful with largest tam
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